Tons. 1) the brilliant researchers working on these models don’t know how to run an ML business 2) cost 3) performance, guardrails, safety 4) infosec/org/legal approval for use in-house 5) power concentration/small talent pool of folks that know this tech
Etc.
REGULATION
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Barriers to Enterprise Adoption of Advanced ML Models
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Meta’s Privacy-Violating Advertising Model Harms Society
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Working at Meta/Facebook isn't a livelihood, it's participating in a giant privacy-violating advertising operation that makes everyone's lives worse
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Responsible AI becomes mandatory skill in job market
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Yup, seems to be true, even saw in job description that have sound understanding of Responsible AI is required, this was not the case earlier
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IBM Emphasizes the Importance of Responsible AI Governance
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In the wake of increasingly accessible and sophisticated #AI models adopting the core principles of AI governance is now critical for the deployment of compliant, reliable, responsible AI. – IBM GM @dineshknirmal → https://ibm.co/3BOGgYS #ChatGPT #datascience #automation
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Legal challenges to discriminatory promotional practices in venues
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Tell that to all the night clubs sued for free women's nights, oh wait…
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AI Artists Must Understand Fair Use Implications Carefully
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This is another reason why AI Artists and companies in this space should not be running around willy-nilly claiming Fair Use without really understanding the consequences.
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Fair Use Defense: Market Harm Burden on Defendants
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Maybe I can bring up a new angle here! Since Fair Use is an affirmative defense, the proof of absence of market harm falls onto the defendants.
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Managing Policy Change on Major Tech Platforms: Leadership Challenges
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bad policy? he'll probably change it if enough people yell at him! because he's like 14 years old emotionally and running a website where everyone hates you if you own it and doing a particularly awful job. it's important but we have to treat it a different way
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Licensing potential in datasets with minimal collection efforts
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You're joking, but there's already 30M to 50M records with licenses (including Creative Commons) and they weren't seriously trying to collect license information. If they actually tried, they'd probably get to 10% 25% or more…
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AI Data Scraping: Programmers Must Track Sources and Copyrights
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You're looking for complexity where there is none. "AI" does not go out in the wild to scrape data, programmers implement code that does it, and thus can & should track the source and copyrights. If there is no clear & usable copyright information, then the code drops it…